I feel like this is more of a math question. I have a programme which visualises distances and then draws them on a map, based on the hue spectre. The problem is that the distance values are not equally distributed and therefore, I only see a few colours of the spectre and it gets quite boring. Attached as photos are the result and the histogram. As you can see, most points are more in the 20-40% range. My code of the colouring function is this one: def colour_gradient_from_distance(distance_array): spectre_size = 1 # number of iterations around rainbow, preferably < 1.0 max_dist = numpy.amax(distance_array) min_dist = numpy.amin(distance_array) rangemm = max_dist - min_dist length = len(distance_array) colours = [None] * length for i in range(length): start = 0 # anything between 0 and 360 hue = ((distance_array - min_dist) / rangemm + (start / 360)) % 1 * spectre_size colours = hue # only hue is changed, the other two are 1.0 return colours It is quite a primitive function, but I have been through like 20 tries. I have tried logarithms, exponentials, linear functions, nothing really fixed this problem. Currently, I am trying to fix exactly this distribution here, but in a perfect world, it would work for all of them. Does anybody have smart inputs to this? Continue reading...
